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The lncRNA Xist forms ∼50 diffraction-limited foci to transcriptionally silence one X chromosome. How this small number of RNA foci and interacting proteins regulate a much larger number of X-linked genes is unknown. We show that Xist foci are locally confined, contain ∼2 RNA molecules, and nucleate supramolecular complexes (SMACs) that include many copies of the critical silencing protein SPEN. Aggregation and exchange of SMAC proteins generate local protein gradients that regulate broad, proximal chromatin regions. Partitioning of numerous SPEN molecules into SMACs is mediated by their intrinsically disordered regions and essential for transcriptional repression. Polycomb deposition via SMACs induces chromatin compaction and the increase in SMACs density around genes, which propagates silencing across the X chromosome. Our findings introduce a mechanism for functional nuclear compartmentalization whereby crowding of transcriptional and architectural regulators enables the silencing of many target genes by few RNA molecules.

RNA, DNA, and protein molecules are highly organized within three-dimensional (3D) structures in the nucleus. Although RNA has been proposed to play a role in nuclear organization, exploring this has been challenging because existing methods cannot measure higher-order RNA and DNA contacts within 3D structures. To address this, we developed RNA & DNA SPRITE (RD-SPRITE) to comprehensively map the spatial organization of RNA and DNA. These maps reveal higher-order RNA-chromatin structures associated with three major classes of nuclear function: RNA processing, heterochromatin assembly, and gene regulation. These data demonstrate that hundreds of ncRNAs form high-concentration territories throughout the nucleus, that specific RNAs are required to recruit various regulators into these territories, and that these RNAs can shape long-range DNA contacts, heterochromatin assembly, and gene expression. These results demonstrate a mechanism where RNAs form high-concentration territories, bind to diffusible regulators, and guide them into compartments to regulate essential nuclear functions.

Nuclear compartments have diverse roles in regulating gene expression, yet the molecular forces and components that drive compartment formation remain largely unclear1. The long non-coding RNA Xist establishes an intra-chromosomal compartment by localizing at a high concentration in a territory spatially close to its transcription locus2 and binding diverse proteins3-5 to achieve X-chromosome inactivation (XCI)6,7. The XCI process therefore serves as a paradigm for understanding how RNA-mediated recruitment of various proteins induces a functional compartment. The properties of the inactive X (Xi)-compartment are known to change over time, because after initial Xist spreading and transcriptional shutoff a state is reached in which gene silencing remains stable even if Xist is turned off8. Here we show that the Xist RNA-binding proteins PTBP19, MATR310, TDP-4311 and CELF112 assemble on the multivalent E-repeat element of Xist7 and, via self-aggregation and heterotypic protein-protein interactions, form a condensate1 in the Xi. This condensate is required for gene silencing and for the anchoring of Xist to the Xi territory, and can be sustained in the absence of Xist. Notably, these E-repeat-binding proteins become essential coincident with transition to the Xist-independent XCI phase8, indicating that the condensate seeded by the E-repeat underlies the developmental switch from Xist-dependence to Xist-independence. Taken together, our data show that Xist forms the Xi compartment by seeding a heteromeric condensate that consists of ubiquitous RNA-binding proteins, revealing an unanticipated mechanism for heritable gene silencing.

The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

As RNA-binding proteins (RBPs) play essential roles in cellular physiology by interacting with target RNA molecules, binding site identification by UV crosslinking and immunoprecipitation (CLIP) of ribonucleoprotein complexes is critical to understanding RBP function. However, current CLIP protocols are technically demanding and yield low-complexity libraries with high experimental failure rates. We have developed an enhanced CLIP (eCLIP) protocol that decreases requisite amplification by ∼1,000-fold, decreasing discarded PCR duplicate reads by ∼60% while maintaining single-nucleotide binding resolution. By simplifying the generation of paired IgG and size-matched input controls, eCLIP improves specificity in the discovery of authentic binding sites. We generated 102 eCLIP experiments for 73 diverse RBPs in HepG2 and K562 cells (available at https://www.encodeproject.org), demonstrating that eCLIP enables large-scale and robust profiling, with amplification and sample requirements similar to those of ChIP-seq. eCLIP enables integrative analysis of diverse RBPs to reveal factor-specific profiles, common artifacts for CLIP and RNA-centric perspectives on RBP activity.

The world's genomics data will never be stored in a single repository - rather, it will be distributed among many sites in many countries. No one site will have enough data to explain genotype to phenotype relationships in rare diseases; therefore, sites must share data. To accomplish this, the genetics community must forge common standards and protocols to make sharing and computing data among many sites a seamless activity. Through the Global Alliance for Genomics and Health, we are pioneering the development of shared application programming interfaces (APIs) to connect the world's genome repositories. In parallel, we are developing an open source software stack (ADAM) that uses these APIs. This combination will create a cohesive genome informatics ecosystem. Using containers, we are facilitating the deployment of this software in a diverse array of environments. Through benchmarking efforts and big data driver projects, we are ensuring ADAM's performance and utility.

Many long non-coding RNAs (lncRNAs) affect gene expression, but the mechanisms by which they act are still largely unknown. One of the best-studied lncRNAs is Xist, which is required for transcriptional silencing of one X chromosome during development in female mammals. Despite extensive efforts to define the mechanism of Xist-mediated transcriptional silencing, we still do not know any proteins required for this role. The main challenge is that there are currently no methods to comprehensively define the proteins that directly interact with a lncRNA in the cell. Here we develop a method to purify a lncRNA from cells and identify proteins interacting with it directly using quantitative mass spectrometry. We identify ten proteins that specifically associate with Xist, three of these proteins--SHARP, SAF-A and LBR--are required for Xist-mediated transcriptional silencing. We show that SHARP, which interacts with the SMRT co-repressor that activates HDAC3, is not only essential for silencing, but is also required for the exclusion of RNA polymerase II (Pol II) from the inactive X. Both SMRT and HDAC3 are also required for silencing and Pol II exclusion. In addition to silencing transcription, SHARP and HDAC3 are required for Xist-mediated recruitment of the polycomb repressive complex 2 (PRC2) across the X chromosome. Our results suggest that Xist silences transcription by directly interacting with SHARP, recruiting SMRT, activating HDAC3, and deacetylating histones to exclude Pol II across the X chromosome.

Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (∼1.5-5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease.

MotivationComparing the genomes from closely related species provides a powerful tool to identify functional elements in a reference genome. Many methods have been developed to identify conserved sequences across species; however, existing methods only model conservation as a decrease in the rate of mutation and have ignored selection acting on the pattern of mutations.ResultsWe present a new approach that takes advantage of deeply sequenced clades to identify evolutionary selection by uncovering not only signatures of rate-based conservation but also substitution patterns characteristic of sequence undergoing natural selection. We describe a new statistical method for modeling biased nucleotide substitutions, a learning algorithm for inferring site-specific substitution biases directly from sequence alignments and a hidden Markov model for detecting constrained elements characterized by biased substitutions. We show that the new approach can identify significantly more degenerate constrained sequences than rate-based methods. Applying it to the ENCODE regions, we identify as much as 10.2% of these regions are under selection.AvailabilityThe algorithms are implemented in a Java software package, called SiPhy, freely available at http://www.broadinstitute.org/science/software/.Supplementary informationSupplementary data are available at Bioinformatics online.

It is clear that RNA has a diverse set of functions and is more than just a messenger between gene and protein. The mammalian genome is extensively transcribed, giving rise to thousands of non-coding transcripts. Whether all of these transcripts are functional is debated, but it is evident that there are many functional large non-coding RNAs (ncRNAs). Recent studies have begun to explore the functional diversity and mechanistic role of these large ncRNAs. Here we synthesize these studies to provide an emerging model whereby large ncRNAs might achieve regulatory specificity through modularity, assembling diverse combinations of proteins and possibly RNA and DNA interactions., More than half a century after being placed as the central component in the flow of genetic information from gene to protein, it is now accepted that RNA can perform [...]

Although thousands of large intergenic non-coding RNAs (lincRNAs) have been identified in mammals, few have been functionally characterized, leading to debate about their biological role. To address this, we performed loss-of- function studies on most lincRNAs expressed in mouse embryonic stem (ES) cells and characterized the effects on gene expression. Here we show that knockdown of lincRNAs has major consequences on gene expression patterns, comparable to knockdown of well-known ES cell regulators. Notably, lincRNAs primarily affect gene expression in trans. Knockdown of dozens of lincRNAs causes either exit from the pluripotent state or upregulation of lineage commitment programs. We integrate lincRNAs into the molecular circuitry of ES cells and show that lincRNA genes are regulated by key transcription factors and that lincRNA transcripts bind to multiple chromatin regulatory proteins to affect shared gene expression programs. Together, the results demonstrate that lincRNAs have key roles in the circuitry controlling ES cell state., The mammalian genome encodes many thousands of large noncoding transcripts1 including a class of ~3,500 lincRNAs identified using a chromatin signature of actively transcribed genes2-4. These lincRNA genes have been [...]

There is growing recognition that mammalian cells produce many thousands of large intergenic transcripts (1-4). However, the functional significance of these transcripts has been particularly controversial. Although there are some well-characterized examples, most (.95%) show little evidence of evolutionary conservation and have been suggested to represent transcriptional noise (5,6). Here we report a new approach to identifying large non-coding RNAs using chromatin-state maps to discover discrete transcriptional units intervening known protein-coding loci. Our approach identified ~1,600 large multi-exonic RNAs across four mouse cell types. In sharp contrast to previous collections, these large intervening non-coding RNAs (lincRNAs) show strong purifying selection in their genomic loci, exonic sequences and promoter regions, with greater than 95% showing clear evolutionary conservation. We also developed a functional genomics approach that assigns putative functions to each lincRNA, demonstrating a diverse range of roles for lincRNAs in processes fromembryonic stem cell pluripotency to cell proliferation. We obtained independent functional validation for the predictions for over 100 lincRNAs, using cell-based assays. In particular, we demonstrate that specific lincRNAs are transcriptionally regulated by key transcription factors in these processes such as p53, NFκB, Sox2, Oct4 (also known as Pou5f1) and Nanog. Together, these results define a unique collection of functional lincRNAs that are highly conserved and implicated in diverse biological processes., There are at present only about a dozen well-characterized lincRNAs in mammals, with transcript sizes ranging from 2.3 to 17.2 kilobases (kb) (7,8). These lincRNAs have distinctive biological roles through [...]

Author(s): Jesse M. Engreitz [1, 2]; Jenna E. Haines [1]; Elizabeth M. Perez [1]; Glen Munson [1]; Jenny Chen [1, 2]; Michael Kane [1]; Patrick E. McDonel [1]; Mitchell Guttman [...]